In digital image processing, several noise reduction methods have been developed in the past in order to improve image quality or the detectability in an image of certain structures of interest. Since in 2-dimensional images noise amplitudes increase with spatial frequency, a rather simple way of noise reduction is the application of a low pass filter which leads to a smoothing of the image. However, this method has the disadvantage, that fine structures are blurred. Another type of filters called nonlinear rank filters significantly reduce blurring effects while effectively reducing salt and pepper noise. However, for Gaussian distributed noise this kind of filtering produces undesired artifacts which are not normally acceptable for diagnostic purposes in medical imaging or in other fields of endeavor that rely on image based information gathering. Also, it is sometimes not in intuitive for a user to understand how a given noise reduction scheme works on an image.